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Adipose tissue, which is the crucial energy reservoir and endocrine organ for the maintenance of systemic glucose, lipid, and energy homeostasis, undergoes significant changes during aging. These changes cause physiological declines and age-related disease in the elderly population. Here, we review the age-related changes in adipose tissue at multiple levels and highlight the underlying mechanisms regulating the aging process. We also discuss the pathogenic pathways of age-related fat dysfunctions and their systemic negative consequences, such as dyslipidemia, chronic general inflammation, insulin resistance, and type 2 diabetes (T2D). Age-related changes in adipose tissue involve redistribution of deposits and composition, in parallel with the functional decline of adipocyte progenitors and accumulation of senescent cells. Multiple pathogenic pathways induce defective adipogenesis, inflammation, aberrant adipocytokine production, and insulin resistance, leading to adipose tissue dysfunction. Changes in gene expression and extracellular signaling molecules regulate the aging process of adipose tissue through various pathways. In addition, adipose tissue aging impacts other organs that are infiltrated by lipids, which leads to systemic inflammation, metabolic system disruption, and aging process acceleration. Moreover, studies have indicated that adipose aging is an early onset event in aging and a potential target to extend lifespan. Together, we suggest that adipose tissue plays a key role in the aging process and is a therapeutic target for the treatment of age-related disease, which deserves further study to advance relevant knowledge.

Nitrogen is one of the most important nutrients needed for plants and algae to survive, and the photosynthetic ability of algae is related to nitrogen abundance. Red algae are unique photosynthetic eukaryotic organisms in the evolution of algae, as they contain phycobilisomes (PBSs) on their thylakoid membranes. In this report, the in vivo chlorophyll (Chl) a fluorescence kinetics of nitrogen-starved Porphyridium cruentum were analyzed to determine the effects of nitrogen deficiency on photosynthetic performance using a multi-color pulse amplitude modulation (PAM) chlorophyll fluorometer. Due to nitrogen starvation, the photochemical efficiency of PSII and the activity of PSII reaction centers (RCs) decreased, and photoinhibition of PSII occurred. The water-splitting system on the donor side of PSII was seriously impacted by nitrogen deficiency, leading to the inactivation of the oxygen-evolving complex (OEC) and decreased light energy conversion efficiency. In nitrogen-starved cells, a higher proportion of energy was used for photochemical reactions, and thermal dissipation was reduced, as shown by qP and qN. The ability of nitrogen-starved cells to tolerate and resist high photon flux densities was weakened. Our results showed that the photosynthetic performance of P. cruentum was severely impacted by nitrogen deficiency.

Cholesterol is an important lipid molecule in cell membranes and lipoproteins. Cholesterol is also a precursors of steroid hormones, bile acids, and vitamin D. Abnormal levels of cholesterol or its precursors have been observed in various human diseases, such as heart diseases, stroke, type II diabetes, brain diseases and many others. Therefore, accurate quantification of cholesterol is important for individuals who are at increased risk for these diseases. Multiple analytical methods have been developed for analysis of cholesterol, including classical chemical methods, enzymatic assays, gas chromatography (GC), liquid chromatography (LC), and mass spectrometry (MS). Strategy known as ambient ionization mass spectrometry (AIMS), operating at atmospheric pressure, with only minimal sample pretreatments for real time, in situ, and rapid interrogation of the sample has also been employed for quantification of cholesterol. In this review, we summarize the most prevalent methods for cholesterol quantification in biological samples and foods. Nevertheless, we highlight several new technologies, such as AIMS, used as alternative methods to measure cholesterol that are potentially next-generation platforms. Representative examples of molecular imaging of cholesterol in tissue sections are also included in this review article.

The subject of this study was to explore the optimum requirements of loach ( Paramisgurnus dabryanus ) regarding dietary proteins and lipids and discuss the underlying mechanism. We designed nine diets to determine the effects of different levels of dietary crude protein (CP: 30%, 35%, and 40%) and ether extract (EE: 6%, 10%, and 14%) on the growth performance and metabolism of P. dabryanus . In total, 2160 healthy P. dabryanus (5.19 ± 0.01 g) were divided into nine groups with four replications at 60 fish per barrel stocking density. The trial lasted for eight weeks. Serum and liver samples were gathered for metabolomic and transcriptomic analyses. The results showed that the specific growth rate of P. dabryanus in the CP40EE10 group was the fastest and notably higher than that in other groups ( P< 0.05). Analysis of the metabolome results found that the mTOR signaling pathway, glycerophospholipid metabolism, D-arginine and D-ornithine metabolism were significantly enriched pathways in the CP40EE10 group compared with the other groups ( P< 0.05). Moreover, the transcriptomic analysis of differentially expressed genes (DEGs) showed that the expression of ARG (arginase) involved in protein synthesis was significantly upregulated in the CP40EE10 group compared to the slowest growing group ( P < 0.05). Additionally, the expression of SPLA2 (secretory phospholipase A2) involved in lipid metabolism and FBP (fructose-1,6-bisphosphatase) involved in glucose metabolism were all significantly downregulated in the CP30EE6 group compared with the CP40EE10 group ( P < 0.05). Furthermore, the analysis of differentially expressed metabolites (DEMs) and DEGs co-enriched in the KEGG pathway revealed that the significantly enriched pathways were arginine and proline metabolism, glycerophospholipid metabolism, and glycolysis/gluconeogenesis in CP40EE10 compared with other groups ( P < 0.05). We conclude that including 40% CP and 10% EE in the P. dabryanus diet could result in a better growth rate. We hypothesized from metabolomic and transcriptomic analyses that the CP40EE10 diet might promote the growth of P. dabryanus by promoting protein synthesis, lipid metabolism, and energy production.

Physiological microenvironments present a time-dependent variation during pathogenic or therapeutic processes, which call for life-like biomaterials of dynamic adaptation. However, current prevailed biomaterials maintain a passively responsive mode and lack autonomous and interactive dynamics. Striving for a paradigm of microenvironment interactive and self-regulatory medical agents as next-generation of biomaterials is of desperate need. Herein, we develop a microenvironment-feedback hydrogel as a living dressing biomaterial catering diabetic chronic wounds. This dynamic hydrogel leverages the initial alkaline pH of the wound bed as fuel and employs biocatalytic acid generation as the anti-fuel. By coupling this feedback loop to pH-regulated imine crosslinks, the hydrogel facilitates adaptive sol-gel cycling with programmable glucose oxidase (GOx) release in a Type-I diabetic mouse model. Thus, homeostatic wound pH and blood glucose levels are achieved, favoring accelerated in vivo wound healing and tissue repair. Chronic wounds typically exhibit dynamic variations within the complex wound microenvironment over time. Here, Cheng et al. develop a microenvironment-feedback hydrogel to achieve homeostatic wound pH and blood glucose levels to accelerate repair of diabetic chronic wounds.

Adipose tissue is a widely distributed organ that plays a critical role in age-related physiological dysfunctions as an important source of chronic sterile low-grade inflammation. Adipose tissue undergoes diverse changes during aging, including fat depot redistribution, brown and beige fat decrease, functional decline of adipose progenitor and stem cells, senescent cell accumulation, and immune cell dysregulation. Specifically, inflammaging is common in aged adipose tissue. Adipose tissue inflammaging reduces adipose plasticity and pathologically contributes to adipocyte hypertrophy, fibrosis, and ultimately, adipose tissue dysfunction. Adipose tissue inflammaging also contributes to age-related diseases, such as diabetes, cardiovascular disease and cancer. There is an increased infiltration of immune cells into adipose tissue, and these infiltrating immune cells secrete proinflammatory cytokines and chemokines. Several important molecular and signaling pathways mediate the process, including JAK/STAT, NFκB and JNK, etc. The roles of immune cells in aging adipose tissue are complex, and the underlying mechanisms remain largely unclear. In this review, we summarize the consequences and causes of inflammaging in adipose tissue. We further outline the cellular/molecular mechanisms of adipose tissue inflammaging and propose potential therapeutic targets to alleviate age-related problems.

Background Recent studies have shown that according to the expression levels of achaete-scute homolog 1 (ASCL1), neurogenic differentiation factor 1 (NEUROD1), and POU class 2 homeobox 3 (POU2F3), small cell lung cancer (SCLC) can be divided into four subtypes: SCLC-A (ASCL1-dominant), SCLC-N (NEUROD1-dominant), SCLC-P (POU2F3-dominant), and SCLC-I (triple negative or SCLC-inflamed). However, there are limited data on the clinical characteristics and prognosis of molecular subtypes of SCLC. Methods Immunohistochemistry (IHC) was used to detect the expression levels of ASCL1, NEUROD1, and POU2F3 in 53 patient samples of resectable SCLC. The subtype was defined by the differential expression of the transcription factors for ASCL1, NEUROD1, and POU2F3 or the low expression of all three factors with an inflamed gene signature (SCLC-A, SCLC-N, SCLC-P, and SCLC-I, respectively). The clinicopathological characteristics, immunological features (programmed death ligand 1 [PD-L1] expression and CD8+ tumor infiltrating lymphocyte [TIL] density), and patient outcomes of the four subtypes of SCLC were analyzed. Results Positive ASCL1, NEUROD1, and POU2F3 staining was detected in 43 (79.2%), 27 (51.0%), and 17 (32.1%) SCLC specimens by IHC. According to the results of IHC analysis, SCLC was divided into four subtypes: SCLC-A (39.6%), SCLC-N (28.3%), SCLC-P (17.0%), and SCLC-I (15.1%). The 5-year overall survival (OS) rates of these four subtypes were 61.9%, 69.3%, 41.7%, and 85.7%, respectively ( P =0.251). There were significant differences in smoking status among different subtypes of SCLC ( P = 0.031). However, we did not confirm the correlation between subtypes of SCLC and other clinicopathological factors or immune profiles. Cox multivariate analysis showed that N stage ( P =0.025), CD8+ TILs ( P =0.024), Ki-67 level ( P =0.040), and SCLC-P ( P =0.023) were independent prognostic factors for resectable SCLC. Conclusions Our IHC-based study validated the proposed classification of SCLC using the expression patterns of key transcriptional regulatory factors. We found that SCLC-P was associated with smokers and was one of the poor prognostic factors of limited-stage SCLC. In addition, no correlation was found between PD-L1 expression or CD8+ TIL density and SCLC subtypes.

With the increasing complexity of modern industrial processes, fault occurrences may lead to catastrophic consequences, making incipient fault detection crucial for industrial safety. This critical task confronts a key challenge: insufficient cross-domain generalization capacity. To overcome this challenge, a feature adaptive ensemble net (FAENet) is proposed by integrating transfer learning with ensemble learning. The framework comprises a feature adaptive extractor (FAE) utilizing convolutional neural networks (CNNs) with maximum mean discrepancy (MMD) for domain-invariant feature extraction, combined with an information entropy gain-based feature screening to filter out redundant and detrimental features. In addition, the famous benchmark Tennessee Eastman process (TEP) and Case Western Reserve University (CWRU) bearing datasets are adopted to demonstrate the performance of the proposed method. For incipient difficult faults 3, 5, 9, 15, 16, and 21 in the TEP, FAENet achieves 99.43% for average fault detection rates (FDRs), exceeding traditional methods of cross-domain fault detection (TCA, JDA, DANN, DTL) by more than 60%. For CWRU’s incipient bearing faults, FAENet achieves 99.4% for FDR, demonstrating significant superiority. This research holds significant practical implications for enhancing the safety and efficiency of industrial systems. It establishes a reliable framework for intelligent fault detection systems across diverse industrial environments, enabling early detection of potential faults to minimize operational risks.

Although many kinds of exopolysaccharides (EPSs) from microorganisms have been used in industry, the exploration and utilization of EPSs from polar microorganisms is still rather rare. In this study, a flavobacterial strain, SM1127, from the Arctic brown alga Laminaria , was screened for its high EPS production (2.11 g/l) and was identified as belonging to the genus Polaribacter . The EPS secreted by strain SM1127 has a molecular mass of 220 kDa and it mainly comprises N -acetyl glucosamine, mannose and glucuronic acid residues bound by heterogeneous linkages. Rheological studies on the aqueous EPS showed that it had a high viscosity and good shear-thinning property. Moreover, the EPS showed a high tolerance to high salinity and a wide pH range. The EPS also had good antioxidant activity. Particularly, its moisture-retention ability was superior to that of any other reported EPS or functional ingredient generally used in cosmetics. The EPS also showed a protective effect on human dermal fibroblasts at low temperature (4 °C). Safety assessment indicated that the EPS is safe for oral administration and external use. These results indicate the promising potential of the EPS from strain SM1127 in the food, cosmetic, pharmaceutical and biomedical fields.

Soybean is one of the most widely grown oilseed crops worldwide. Several unfavorable factors, including salt and salt–alkali stress caused by soil salinization, affect soybean yield and quality. Therefore, exploring the molecular basis of salt tolerance in plants and developing genetic resources for genetic breeding is important. Sucrose non-fermentable protein kinase 1 (SnRK1) belongs to a class of Ser/Thr protein kinases that are evolutionarily highly conserved direct homologs of yeast SNF1 and animal AMPKs and are involved in various abiotic stresses in plants. The GmPKS4 gene was experimentally shown to be involved with salinity tolerance. First, using the yeast two-hybrid technique and bimolecular fluorescence complementation (BiFC) technique, the GmSNF1 protein was shown to interact with the GmPKS4 protein. Second, the GmSNF1 gene responded positively to salt and salt–alkali stress according to qRT-PCR analysis, and the GmSNF1 protein was localized in the nucleus and cytoplasm using subcellular localization assay. The GmSNF1 gene was then heterologously expressed in yeast, and the GmSNF1 gene was tentatively identified as having salt and salt–alkali tolerance function. Finally, the salt–alkali tolerance function of the GmSNF1 gene was demonstrated by transgenic Arabidopsis thaliana, soybean hairy root complex plants overexpressing GmSNF1 and GmSNF1 gene-silenced soybean using VIGS. These results indicated that GmSNF1 might be useful in genetic engineering to improve plant salt and salt–alkali tolerance.